Dynamic modeling of COVID effects on labor-management negotiations

We present results of an interdisciplinary study of labor-management negotiations (LMN). The analysis of this complex process focuses on French LMN. First, we developed a dynamic, multiplex network model to map multi-group interactions in time under different contextual conditions, for negotiators to explore scenarios of expected outcomes and develop strategies. Second, we estimated the model’s parameters for a multinational company, using in-depth interviews with key negotiators, survey data, company documents and participant observations in France. We generated anticipatory scenarios of the negotiations’ trajectories in time under various context assumptions. Here, we use the model to explore whether/how the global COVID pandemic has affected LMN. We hypothesize pandemic impacts on the context, inter-relations and dynamics of LMN, resulting from rising unemployment, budgetary and regulatory constraints, and a sharp drop in the French company’s sales. With new qualitative data, we re-examine negotiation trajectories and outcomes and compare them to pre-COVID results.